SRI-summer-internship

SRI-summer-internship

SRI International: Research Internships in Artificial IntelligenceSummer 2018The Artificial Intelligence Center at SRI International is hiring for the research intern positions describedbelow. Positions are available in both Menlo Park, CA, and San Diego, CA. Interested parties shouldcontact Nick Marozick (nick.marozick@sri.com) for further details.

Positions in Menlo Park, CAExplainable Autonomy. With the powerful but opaque nature of today’s AI algorithms, interpretabilityhas become a hot topic. The Explainable Autonomy project tackles the problem of autonomous agentsknowing when, what, and how to explain their behavior to human collaborators. We are looking for asummer intern with a keen interest in collaborative AI to develop ideas and implement technology forexplainable autonomy. You will be working with experts in autonomy, machine learning, and humancomputerinteraction to design and build explainable systems. Programming experience andknowledge of machine learning and/or autonomous agents a must; familiarity with reinforcementlearning a plus.Proactive Decision Support. Intelligent assistant technology today is primarily user-driven, with thesystem simply responding to explicit user commands. The Proactive Decision Support project aims todevelop capabilities to enable an intelligent system to take the initiative and provide timely, contextrelevantassistance to users. We are looking for a summer intern with innovative ideas and excellentprogramming skills to develop and implement algorithms for proactive decision support. Prior andplanned research threads for the project include sequential pattern mining, plan recognition, and textanalytics. Programming experience and knowledge of machine learning algorithms a must; familiaritywith text analytics a plus.Whole-body Person Recognition. This project seeks to recognize people from whole-body videos,exploiting aspects of body shape and motion. The research will include both the development andevaluation of a state-of-art identification system on existing data collections, as well as a moresystematic exploration of the effects of difficult viewing conditions on whole-body identification byusing rendered 3D motion capture data. Our objectives are both to push the state of the art as well asto understand the nature of the problem as an aid to future research programs.Detection of Tampered Videos. The goal is to detect tampering of videos, such as the replacement of asegment of audio or the replacement of a sequence of video frames. The research will focus ontechniques that combine extracted descriptions of both the audio and visual components of a video,pinpointing discrepancies between them. For example, and audio analysis indicating that the audiowas recorded in a small room (by examining reverberation properties of the audio track) combinedwith a visual analysis indicating that the scene is outdoors could indicate tampering.

Positions in San Diego, CAFriendly Bot. The aim of this project is to develop a natural language dialog capability thatemulates the response of typical native speakers of American English to communications fromindividuals unknown to them. The intern will study available communication corpora and develop amodest domain theory that encompasses a handful of intents and language acts relevant to a botresponding in a friendly fashion to overtures from unknown individuals. We will then experimentwith approaches to producing a bot capable of conducting dialog according to this theory. Ofgreatest interest are approaches that attempt to backfit neural chit-chat models trained on largedialog corpora to the domain theory. Experience with NLP research, ideally in NL dialogue isrequired. Familiarity and experience with neural approaches to language modeling is a plus.Twitter Event Processing. The aim of this project is to assess the impact of events in the news ondiscussions found in social media, particularly twitter. The intern will develop algorithms to resolvereferences to events in twitter to news articles and to classify and extract relevant details aboutthose events, as reported in the news, for the purpose of assessing their impact in the form oftwitter buzz. The intern will also create methods for assessing the magnitude of response to anarticle, ideally with reference to inferred demographic or personality factors of the respondingusers. Experience with NLP research, social media, machine learning is required. Familiarity withrelevant social science research is of interest.Knowledge Base Population. The goal of this project is to develop a natural language processingsystem that can automatically create a formal knowledge base from unstructured textualinformation found on the Web. The intern will integrate existing SRI text analytic softwarecomponents, including text classification, language modeling, entity set expansion, term similarityassessment, and information extraction into a coherent active learning architecture for knowledgebase population. Experience in NLP, machine learning, and Java programming is required.Experience in linguistics and knowledge representation is a bonus.Inline Evidence for Automated Writing Assessment. The goal of this project is to enhance anexisting SRI automated essay scoring software platform with a new capability for highlighting anddescribing evidence of the system's decisions. The intern will investigate methods for determiningthe influence of extracted text features on machine learning module predictions and pair this withthe development of a new capability for tracing the provenance of features back to the portions oftext from which they originate, and describing that provenance to end users. This will enhanceautomated student feedback with more practical explanations that students can use to improvetheir writing. Experience in NLP, machine learning, and Java programming is required. Experience inlinguistics and writing assessment is a bonus.Novel Deep Learning Architectures. The goal of this project is to develop network construction andtraining techniques with improved optimization behavior. We are currently conducting research onthe construction of adaptive networks that simultaneously model both empirical data andformalized knowledge. The intern will study the impact of network properties and regularizationtechniques on the convergence of optimization algorithms and quality of solutions. Experience withnetwork implementation, training and evaluation, either in Theano or TensorFlow, familiarity withmachine learning techniques, and experience working with large datasets is preferred.